🤖 question-answering

electra_large_discriminator_squad2_512

ahotrod/electra_large_discriminator_squad2_512

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transformers
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Model Details
Full Model IDahotrod/electra_large_discriminator_squad2_512
Pipeline / Taskquestion-answering
Librarytransformers
Downloads (all-time)888.7K
Likes7
Last Modified12/11/2020
Author / Orgahotrod
PrivateNo — public
⚡ Quick Usage (Python)

Using the 🤗 Transformers library. Install with pip install transformers

from transformers import pipeline

# Load the model
pipe = pipeline("question-answering", model="ahotrod/electra_large_discriminator_squad2_512")

# Run inference
result = pipe("Your input here")
print(result)
🏷️ Tags
transformerspytorchtfelectraquestion-answeringendpoints_compatibledeploy:azureregion:us
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🚀 Use This Model

Access model files, inference API, and full documentation on Hugging Face.

Open on Hugging Face →Browse Model Files ↗← Browse All Models
🤖 Task: question-answering

This model is designed for the question-answering task. Explore more models for this use case.

All question-answering Models →
📊 Popularity
Downloads888.7K
❤️ Community Likes7
🛠️ Requirements
  • Install: pip install transformers
  • Python 3.8+ recommended for Transformers.
  • GPU (CUDA) speeds up inference significantly.
  • Use model.half() for fp16 on limited VRAM.
👋 Need help with code?